System Design Process Research Articles

Designing with words: Writing as design

Writing for design has, over the past few decades, seen steady appreciation. Literature on design writing refers to it as a mostly technical vocation centred on the craft of writing in and of itself. Moreover, the suggestion seems to be that while writing is beneficial to, it is also distinct from the practice of communication design. Elsewhere, writing in the context of communication design is viewed as a specialisation - a skill that is typically reserved for a specialist writer who helps craft a tone to complement a predominantly visual design. In this article, we argue that writing for design is a far more complex and foundational skill for communication designers. In doing so, we explore the interdependence of narrative and writing, as a systematic design process and so highlight the importance of creative writing as design in an educational context and emphasise how integral writing is to the designer as a storyteller. To demonstrate this, we explore a selection of student work from an editorial project that has, for the past 21 years, been delivered to fourth-year Information Design students at the University of Pretoria (and which formed part of the 2023 Stories Worth Telling retrospective exhibition).

BLE Bluetooth remote-controlled car based on ESP32

Abstract. With the rapid advancement of information technology, Bluetooth technology has been widely used in the field of short-range wireless communication, playing an important role in information exchange. As one of the main technologies for short-range wireless communication, Bluetooth technology has broad application prospects, especially in robotic applications such as remote-controlled cars. This paper provides a detailed introduction to the design and implementation process of a Bluetooth remote-controlled car system based on the ESP32. It covers the classic Bluetooth and Bluetooth Low Energy (BLE) functionalities of the ESP32, the hardware design and assembly of the car (including the DC motor drive module, Bluetooth module, and speed measurement module), and methods for establishing a connection between the ESP32 and Bluetooth module, data transmission, and remote control of the car's movement. The paper also evaluates the system's performance through experiments, discusses the application and parameter adjustment of the PID control algorithm in enhancing speed control, and finally summarizes the research findings and suggests directions for future work.

An automated AI-powered IoT algorithm with data processing and noise elimination for plant monitoring and actuating

This article aims to develop a novel Artificial Intelligence-powered Internet of Things (AI-powered IoT) system that can automatically monitor the conditions of the plant (crop) and apply the necessary action without human interaction. The system can remotely send a report on the plant conditions to the farmers through IoT, enabling them for tracking the healthiness of plants. Chili plant has been selected to test the proposed AI-powered IoT monitoring and actuating system as it is so sensitive to the soil moisture, weather changes and can be attacked by several types of diseases. The structure of the proposed system is passed through five main stages, namely, AI-powered IoT system design, prototype fabrication, signal and image processing, noise elimination and proposed system testing. The prototype for monitoring is equipped with multiple sensors, namely, soil moisture, carbon dioxide (CO2) detector, temperature, and camera sensors, which are utilized to continuously monitor the conditions of the plant. Several signal and image processing operations have been applied on the acquired sensors data to prepare them for further post-processing stage. In the post processing step, a new AI based noise elimination algorithm has been introduced to eliminate the noise in the images and take the right actions which are performed using actuators such as pumps, fans to make the necessary actions. The experimental results show that the prototype is functioning well with the proposed AI-powered IoT algorithm, where the water pump, exhausted fan and pesticide pump are actuated when the sensors detect a low moisture level, high CO2 concentration level, and video processing-based pests’ detection, respectively. The results also show that the algorithm is capable to detect the pests on the leaves with 75% successful rate.

Selecting sustainable packaging materials and strategies: A holistic approach considering whole life cycle and customer preferences

With the increasing public awareness of packaging and the environmental impact caused by it, companies are driving their businesses to introduce and promote practices that help ease the negative impact of packaging on the environment. Studies done on consumer behaviour show that decisions nowadays are influenced by sustainability. Yet, companies struggle with changing practices and justifying adopting environmentally friendly packaging materials. The current paper presents a holistic approach, addressing the need for identifying, assessing, and selecting sustainable materials for packaging applications. The Kano model prioritises features that are then used with Ashby plots for identifying alternative materials. Life cycle assessment, as well as life cycle costing, are used for assessing the environmental and financial impact of the use of such materials. Automatically weighted Multi-Criteria Decision-Making Analysis (MCDA) is used to select the most appropriate packaging material. This methodology provides a combinatorial ranking for each criterion set by four pre-defined weight distributions for Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS). The proposed methodology allows for a systematic and holistic design process when deciding on packaging materials for any product. The methodology is validated for the case of packaging weather-sensitive cast stone products and carbonated drinks. In cast stone, three packaging materials are ranked for pallets based on their attributes. Similarly, for carbonated drinks, three packaging materials are recommended at the end of the study.

Design and Implementation of a 7-Person Voting Device based on Quartus

As the complexity of digital system design continues to increase, efficient and precise decision support systems have become increasingly important. This paper presents the design and implementation of a 7-voter decision system based on Altera’s Quartus software. The voter is applied in the core decision-making process to ensure the accuracy and efficiency of decisions. The study begins by outlining the design principles of the 7-voter decision system, using a design philosophy that minimizes timing delays and optimizes hardware resource utilization. A complex majority voting logic circuit is implemented using high-level hardware description languages (VHDL/Verilog), ensuring the advanced nature and applicability of the voting circuit. In terms of the logical implementation of the voting circuit, the paper conducts an in-depth analysis of the optimization of combinational and sequential logic and standardizes the input and output to enhance the signal stability and the system’s resistance to interference. On the Quartus platform, the design process of the voting system is elaborated in detail, with careful consideration given to boundary conditions and hardware compatibility. The implementation of the voter has undergone rigorous simulation and testing. Strict parameter setting for simulations and waveform analysis confirm the correctness of the circuit, and fault simulation tests further confirm its reliability. Performance indicators such as response time and percentage of resource utilization have been quantitatively analyzed and meet the design objectives set beforehand. Overall, this research not only realizes a highperformance 7-voter decision system but also provides an effective case study for applications on the high-performance Quartus design platform. Future research can build on the current work to further optimize algorithms and hardware, explore the potential for the application of the voter in a broader range of fields, and adapt to the new features of the Quartus platform to achieve more powerful decision support functions.

An innovative dynamic observer for nonlinear interconnected systems with uncertainties

In this paper, an innovative dynamic observer is applied to complex nonlinear interconnected systems with matched and mismatched uncertainties. This dynamic observer can estimate system states, which cannot be achieved during the design process for nonlinear interconnected systems with uncertainties. The proposed method has great identification ability with small estimated errors for the states of nonlinear interconnected systems with matched and mismatched uncertainties. It should be pointed out that the considered uncertainties of nonlinear interconnected systems have general forms, which means that the proposed method can be effectively used in more generalised nonlinear interconnected systems. Finally, simulation results for the lateral flight control system are presented to ensure the effectiveness of this strategy.

Model predictive control for space robot manipulator modeled by switched systems: A data‐driven approach

AbstractThis article investigates the data‐driven based model predictive control (MPC) problem for a class of space robot manipulator (SRM). First, the SRM system is modeled as a class of discrete‐time switched system to reflect more system characteristics. Second, only the input‐state data are used for end‐to‐end controller design, and the system identification process is avoided. In order to meet the real‐time requirements of the manipulator arm angles, a kind of constrained predictive control method is designed to prevent the overheating or damage of SRM motor, optimizing the cost function for each decision cycle under the safe control input constraints. Then, based on the average dwell time method, the asymptotic stability is assured for the presented SRM system. The design conditions for data‐driven based MPC are provided in the form of linear matrix inequalities. Finally, the effectiveness and advantage for the developed data‐driven based MPC strategy are validated via a case study of SRM system.

Cyber Resilience Limitations in Space Systems Design Process: Insights from Space Designers

Space technology is integral to modern critical systems, including navigation, communication, weather, financial services, and defence. Despite its significance, space infrastructure faces unique cyber resilience challenges exacerbated by the size, isolation, cost, persistence of legacy systems, and lack of comprehensive cyber resilience engineering standards. This paper examines the engineering challenges associated with incorporating cyber resilience into space design, drawing on insights and experiences from industry experts. Through qualitative interviews with engineers, cybersecurity specialists, project managers, and testers, we identified key themes in engineering methodologies, cybersecurity awareness, and the challenges of integrating cyber resilience into space projects. Participants emphasised the importance of incorporating cybersecurity considerations from the earliest stages of design, advocating for principles such as zero-trust architecture and security by design. Our findings reveal that experts favour Model-Based Systems Engineering (MBSE) and Agile methodologies, highlighting their synergy in developing flexible and resilient systems. The study also underscores the tension between principles-based standards, which offer flexibility but can lead to inconsistent implementation, and compliance-based approaches, which provide clear measures but may struggle to adapt to evolving threats. Additionally, the research recognises significant barriers to achieving cyber resilience, including insider threats, the complexity of testing and validation, and budget constraints. Effective stakeholder engagement and innovative funding models are crucial for fostering a culture of cybersecurity awareness and investment in necessary technologies. This study highlights the need for a comprehensive cyber resilience framework that integrates diverse engineering methodologies and proactive security measures, ensuring the resilience of space infrastructure against emerging cyber threats.

Molecular simulation of gas entrapment near a nanoscale cavity: The interplay of surface wettability, cavity shape, and gas type

Surface cavities play a crucial role in trapping and stabilizing gases, a phenomenon that can be used to facilitate applications in separation and drying processes. Understanding surface characteristics in relation to fluid-surface interactions is essential for designing interfacial properties that enable effective processes. In this work, we adopt a molecular simulation approach to investigate gas adsorption and entrapment in surface defects (cavities), focusing on the influence of surface wettability, cavity shape, and gas type. For this purpose, two types of silica-based surfaces with different levels of wettability (methylated and hydroxylated, with the former having lower water wettability), two cavity shapes with identical opening width and depth (V-shaped and square-shaped), and two types of gas (carbon dioxide and nitrogen) are considered. Our observations indicate that a stable gas nanobubble forms when a methylated surface combines with a square-shaped cavity, regardless of the gas type. In contrast, for hydroxylated surface, gas type becomes important; in a square-shaped cavity, nitrogen forms a stable nanobubble while CO2 is trapped in a monolayer fashion. The interfacial forces between the gas and surface which affects gas configuration near the surface, along with the gas molecules’ self-interaction manifested by solubility, are key to the different entrapment modes for N2 and CO2. Moreover, the square-shaped cavity exhibits better capability in trapping gas compared to the V-shaped cavity due to its higher surface area and smaller opening-to-interior ratio. The results of our molecular simulations can guide the design of surface features and processing systems to modify gas entrapment modes and stabilize nanoscale gas bubbles without altering thermodynamic conditions or fluid properties.

Design and implementation of the international news commentary Data Intelligent Processing System

In the digital media age, international news commentary has changed, creating challenges such as information overload and noise. Traditional platforms often need more data-driven analysis capabilities. This study presented a specialized intelligent system for processing international news commentary data. The system provided robust analysis tools, automated recommendations, and summarization capabilities. Its comprehensive modules included data crawling, processing, visualization, and retrieval. Experimental results demonstrated the system’s effectiveness in processing data and generating valuable insights. Users were able to gain objective insights into topics, emotions, and dissemination patterns. The system provided valuable resources for communication research, enhancing theoretical understanding and practical applications in the field.

Digital Educational Escape Rooms as E-courses Using D-EER4SmL: Investigation of Motivational Affordances

Research has shown that educational escape rooms (EERs) motivate and engage learners in the learning process, mainly due to the incorporation of game elements into their educational context. As a result, various frameworks have been proposed to design and develop EERs over the past few years. However, these frameworks fail to highlight the important "D"-digital factor of technology which transforms EERs into Digital Educational Escape Rooms (DEERs), as well as the smart pedagogy (SmP), which in turn goes beyond game-based approaches and is currently essential for the design and the development of well-orchestrated and reusable smart learning solutions. Due to the fact that technology increases motivation, this study introduces the work-in-progress framework D-EER4SmL, primarily based on John Keller's theory of ARCS and the 10-step systematic design process for the development of motivational e-courses, tailored to learners' preferences. The framework was aligned with various EER design principles, along with Smart Pedagogical (SmP) approaches, which could be facilitated by web technologies in order to design and develop DEERs as e-courses. To confirm the motivational aspect of smart learning and the assumption that digital technology provides additional motivation, a DEER e-course was developed, based on this framework. The DEER e-course was delivered to ICT students - future ICT teachers/e-learning educators - who would be trained in instructional/e-learning design utilizing web technologies. A total of 108 higher education students of digital systems voluntarily participated in the workflows of the DEER e-course, played the game, and evaluated motivational affordances (MAs), after completing it. Quantitative data analysis was conducted, based on an improvised questionnaire for DEERs, aligned with Keller’s Instructional Materials Motivation Survey (IMMS). As far as motivation is concerned, the framework was proven effective in the initial research findings; however, further research is needed to confirm its effectiveness within the wider context of smart learning.

An integrated systematic method for interlaced unmanned spatial systems (IUSS) design process

Unmanned Aerial Systems (UAS) have garnered significant interest in recent years. These systems, commonly consisting of one or more Unmanned Aerial Vehicles (UAV) and satellite systems, have been extensively used to enhance the effectiveness of various SOSs, such as disaster management and relief efforts. In addition, the inaugural Mars unmanned helicopter, Ingenuity (Ginny), successfully took flight in April 2021, marking the beginning of the utilization of these systems on Mars. This research aims to build an integrated approach for developing Interlaced Unmanned Spatial Systems, considering the high level of precision required for space systems. This study aims to set up and optimize all parts of the proposed architecture for the design of IUSS, using Model-Based Systems Engineering theories and Dependency Structural Matrix foundations. This research introduces a comprehensive coherence architecture that considers all design domains, including the design process, design office, products, and requirements. Additionally, a design workflow model is provided.

Visualising the school: a critical study on co-designing a Moodle-based learning management system

ABSTRACT Critical research on data visualisations in education has so far mostly focused on the representation of numeric data in dashboards or graphs. Consequently, the question of how schools are made visible and (re)enacted through visual structures on data-mediated interfaces more broadly – what we call Graphic Data Visualisations (GDV) – has remained under-researched. Addressing that research gap, this study specifically scrutinises the role of GDV as non-human actors within the design process of a Moodle-based learning management system (LMS) in four schools. Following a critical co-design approach, the potential of GDV to reflect on how the visual design shapes educational practices, and to adapt it according to pedagogical and organisational needs is explored. Focusing on ‘critical incidents’ in the design process, we found that local practices substantially influenced the data-based, visual enactment of a school through specific GDV. At the same time, the use of certain GDV enhanced a general critical engagement with datafication among school actors.

Accurate solar radiation site adaptation: Harnessing satellite data and in situ measurements

Accurate solar radiation data are essential to optimize solar energy systems and assess their feasibility. In this study, we propose a site-adaptation procedure based on a machine learning model trained to enhance the accuracy of solar radiation data using a combination of the National Solar Radiation Database (NSRDB) and in situ data collected in southern Colombia. The NSRDB provides high temporal and spatial resolution data, while in situ data offer accurate localized measurements specific to the study area. Our machine learning models were trained to learn the relationships between NSRDB data and in situ meteorological station data. The results demonstrate promising predictive capabilities, with the extreme grading boosting model effectively reducing mean absolute error, while a neural network model trained with the triplet loss function proved effective in minimizing mean bias error (MBE) and improving correlation between model-adjusted and in situ collected data. These findings make significant contributions to the field of solar radiation prediction, highlighting the effectiveness of amalgamating NSRDB and in situ data for precise solar radiation estimation, and promote the advancement of solar energy system design and decision-making processes.

Research on parameter selection criteria and design method for leachate pumping using vertical shafts

High leachate levels in landfills not only threaten the environment but also seriously affect the stability of piles. Therefore, it is crucial to pump leachate from piles, and vertical pumping wells have demonstrated their effectiveness in practical engineering. This paper establishes a model of vertical pumping wells, taking into account the non-homogeneous distribution of geotechnical parameters of the pile. The accuracy of this model is then validated through existing test results and numerical models. The main findings of the study are as follows: the radius of influence R is primarily influenced by the pumping time T, pumping pressure P, and anisotropy coefficient A. On the other hand, the depth of influence h is mainly determined by the burial depth h1 of the pumping section. The optimal pumping time Tb coincides with the time at which the well reaches its maximum radius of influence Rm. Similarly, the optimal pumping pressure Pb corresponds to the inflection point in the relationship between the radius of influence R and the pumping pressure P. The optimal pumping section burial depth is h1b = 20 m, and the optimal setback distance db is equal to the maximum setback distance dm. Additionally, this paper provides the criteria for parameter selection under each working condition at the optimal burial depth of the pumping section, as well as the design process for the vertical pumping system. The parameter design diagram and design method presented in this paper serve as valuable references for the design of real guide drainage projects.

Text-to-Model Transformation: Natural Language-Based Model Generation Framework

System modeling language (SysML) diagrams generated manually by system modelers can sometimes be prone to errors, which are time-consuming and introduce subjectivity. Natural language processing (NLP) techniques and tools to create SysML diagrams can aid in improving software and systems design processes. Though NLP effectively extracts and analyzes raw text data, such as text-based requirement documents, to assist in design specification, natural language, inherent complexity, and variability pose challenges in accurately interpreting the data. In this paper, we explore the integration of NLP with SysML to automate the generation of system models from input textual requirements. We propose a model generation framework leveraging Python and the spaCy NLP library to process text input and generate class/block definition diagrams using PlantUML for visual representation. The intent of this framework is to aid in reducing the manual effort in creating SysML v1.6 diagrams—class/block definition diagrams in this case. We evaluate the effectiveness of the framework using precision and recall measures. The contribution of this paper to the systems modeling domain is two-fold. First, a review and analysis of natural language processing techniques for the automated generation of SysML diagrams are provided. Second, a framework to automatically extract textual relationships tailored for generating a class diagram/block diagram that contains the classes/blocks, their relationships, methods, and attributes is presented.

Flap Monitoring Techniques: A Review.

Postoperative tissue flap vitality monitoring enables early detection of clinical complications, allowing for intervention. Timely re-operation can prevent the need for extensive correction procedures, thus reducing healthcare costs and hospitalization time. Statistics show that monitoring can increase the success rate of flap survival to 95% or higher. However, despite the significant progress in monitoring techniques, major and minor complications, leading to the loss of the flap, still occur. This clinical application review aims to provide a comprehensive overview of the recent advancements and findings in flap surgery reconstructions, transplants, and systems for their postoperative assessment. The literature from the years 1925 to 2024 has been reviewed to capture previous and current solutions for monitoring flap vitality. Clinically acclaimed methods and experimental techniques were classified and reviewed from a technical and clinical standpoint. Physical examination, metabolism change, ultrasound method, and electromagnetic (EM) radiation-based measurement methods were carefully evaluated from the perspective of their considered applications. Guidelines aiding engineers in the future design and development process of monitoring systems were proposed. This paper provides a comprehensive overview of the monitoring techniques used in postoperative flap vitality monitoring. It also gives an overview of each approach and potential ways for future development.

Robust active vibration control of flexible smart beam by μ-synthesis

This paper presents a comprehensive method for designing a robust active vibration control system to suppress low-frequency vibrations in smart structures. A novel finite element method based on the first-order shear deformation theory is used to calculate the dynamic response of a smart beam. Through a comprehensive system identification process, the uncertain model of the smart beam is extracted considering both the magnitude and phase. The model fits the experimental data successfully. In addition, a generalized low-frequency vibration control performance function is designed for the piezoelectric smart beam. Using a linear fractional transformation, the system is converted into a standard μ-synthesis control framework, and the controller K is synthesized using structural singular values μ. The effectiveness of the proposed method is experimentally validated using a setup with a piezoelectric smart beam. The experimental results suggest that the proposed control method exhibits robust stability and robust performance, effectively enhancing the performance of smart structure control in various scenarios. The proposed control framework utilizes structured singular value analysis to provide optimal robust stability margins and superior robust control performance, effectively addressing system uncertainties and non-linearities.

Teaching experience for process identification using first‐order‐plus‐time‐delay models

AbstractThis paper introduces an instructional framework for process identification, combining theoretical concepts with practical laboratory exercises, focusing particularly on the identification of first‐order‐plus‐time‐delay models. Our methodology emphasizes guiding students through the various stages involved in the system identification process, namely mastering techniques, such as data acquisition and preprocessing, identification and validation stages, and method comparison. The laboratory assignment is structured into three distinct stages: an initial prelab task working with simulated data, the hands‐on work with laboratory equipment, and the assignment report writing and oral presentation. The assessment of students' learning outcomes is conducted using a detailed rubric. Feedback from a focus group interview indicates that the majority of students appreciated the well‐balanced content, highlighting a strong link between theoretical concepts and practical application.

Correlation Statistics and Parameter Optimization Algorithms for RIS-Assisted Marine Wireless Communication Systems

Reconfigurable intelligent surfaces (RISs), as one of the potential key technologies in sixth generation (6G) mobile communications, feature low costs, low energy consumption, and ease of deployment. In this paper, we introduce the RIS technology into the maritime wireless communication scenario, which can transform the wireless transmission environment from uncontrollable to controllable. In the considered communication model, we derive the complex channel impulse response for the RIS propagation link and non-line-of-sight propagation link, respectively. This can be used to capture the physical properties of a communication model from different perspectives. Furthermore, based on the designed communication model, we investigate the correlation properties of propagation links in the space and time domains; they are the space correlation statistics and time correlation statistics. The provided framework addresses the technical bottleneck of the existing RIS channel modeling methods that fail to balance precision and efficiency, improves the channel model matching efficiency in the design process of RIS-enabled near-field maritime communication systems, and provides technical support for the rapid development of the 6G mobile communication industry.